Distributed and Big Data Storage Management in Grid Computing
Big data storage management is one of the most challenging issues for Grid computing environments, since large amount of data intensive applications frequently involve a high degree of data access locality. Grid applications typically deal with large amounts of data. In traditional approaches high-performance computing consists dedicated servers that are used to data storage and data replication. In this paper, the authors present a new mechanism for distributed and big data storage and resource discovery services. Here they proposed an architecture named Dynamic and Scalable Storage Management (DSSM) architecture in grid environments. This allows in grid computing not only sharing the computational cycles, but also share the storage space.